Development of a Theoretical Model for the Breathability of Textile Fabrics
Abstract
The objective of this study is to develop a theoretical model for predicting the breathability of textile fabrics, with a particular focus on their structural properties and airflow dynamics. Textile fabrics are employed in a multitude of fields, including fashion, medicine, and industry. Consequently, an understanding of their breathability is of paramount importance for a plethora of applications. The research identifies the key factors influencing breathability, including material density, thickness, porosity, and fibre geometry. The study primarily examines factors such as material density, thickness, porosity, and fibre geometry, with additional consideration of potential influences on breathability, including fibre type and fabric finishing treatments. This approach provides a more comprehensive understanding of the factors affecting breathability. The model incorporates the concept of a porous “ideal stone” system and applies the Poiseuille formula for capillary flow to describe the movement of air through textiles. The Poiseuille formula is relevant in that it is capable of representing airflow through a system of parallel capillaries, thereby accounting for the laminar flow that is observed in textile materials. The porous “ideal stone’ system serves to model the internal structure of the fabric, thereby facilitating a detailed understanding of the patterns of airflow and pressure variation across a range of textiles. The findings indicate that a loop model, which accounts for the cross-sectional shape of fibres at the thread level, provides a more accurate representation of airflow behaviour. Testing of elastic knitwear samples in standardized conditions showed loop spacing of approximately 1.58 mm, contrasting with theoretical calculations that suggested 2.14 mm gaps between loops. All tests were conducted at 20°C ± 2°C with 65% ± 4% humidity. The outcomes of this study have practical applications in optimizing textile design, allowing for better recommendations on fabric selection based on specific breathability requirements.
Article Metrics
Abstract: 171 Viewers PDF: 142 ViewersKeywords
Full Text:
PDFRefbacks
- There are currently no refbacks.
Journal of Applied Data Sciences
ISSN | : | 2723-6471 (Online) |
Organized by | : | Computer Science and Systems Information Technology, King Abdulaziz University, Kingdom of Saudi Arabia. |
Website | : | http://bright-journal.org/JADS |
: | taqwa@amikompurwokerto.ac.id (principal contact) | |
support@bright-journal.org (technical issues) |
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0